1. Field of the Invention
The present invention relates to a process control system, and more particularly to a process control system for realizing the optimal process coordinate control.
2. Description of the Related Art
FIG. 56 shows an example of a conventional process control system which is a multi-input/output control system including a main input provided with an optimal operation decision means.
The conventional example shown in FIG. 56 will be explained hereunder. A process 5609 to be controlled is composed of a first fuel control valve 5610, a first boiler 5611, a control valve 5612, a turbine 5613, a generator 5614, a second fuel control valve 5615, a second boiler 5616, and a steam load facility 5617.
A control system 5600 is composed of an optimization model storage unit 5601, an optimal operation decision means 5602, a generator output control means 5605, a first boiler steam pressure control means 5606, and a second boiler steam pressure control means 5607.
The optimal operation decision means 5602 inputs an process data input 5638 inputted from the process 5609 to be controlled and an optimization model 5630 stored in the optimization model storage unit 5601, and decides an optimal operating point for the process operation. The optimization model 5630 stored in the optimization model storage unit 5601 is expressed by Formula 1. Here, Formula 1 is composed of an objective function formula 1a and constraint function formulas 1b to 1g.
The optimal operation decision means 5602 decides the optimal operating point for the process operation using the optimization model 5630 expressed by Formula 1.
Formula 1
Minimize:
X1+X2xe2x80x83xe2x80x83(1a)
Subject to:
X1minxe2x89xa6X1xe2x89xa6X1maxxe2x80x83xe2x80x83(1b)
X2minxe2x89xa6X2xe2x89xa6X2maxxe2x80x83xe2x80x83(1c)
Y1+Y3=Lxe2x80x83xe2x80x83(1d)
Y1=a1(0)+a1(1)xc3x97X1+a1(2)xc3x97X12xe2x80x83xe2x80x83(1e)
Y2=a2(0)+a2(1)xc3x97X1+a2(2)xc3x97X12xe2x80x83xe2x80x83(1f)
Y3=a3(0)+a3(1)xc3x97X2+a3(2)xc3x97X22xe2x80x83xe2x80x83(1g)
In Formula 1, X1, X1min and X1max indicate a flow, a minimum flow and a maximum flow of a fuel 5620 of the first boiler 5611, respectively. X2, X2min and X2max indicate a flow, a minimum flow and a maximum flow of a fuel 5626 of the second boiler 5616, respectively. Y3 indicates a steam flow at an outlet 5625 of the second boiler 5616. Y1 and Y2 indicate a steam flow of a turbine exhaust 5623 and a generation output 5635 of the generator 5614, respectively. L indicates a steam flow 5627 of the steam load facility 5617. The steam flow 5627 (L) is inputted to the optimal operation decision means 5602 from the process 5609 as a part of the process data input 5638.
By converting the units of the variables X1, X2, Y1, Y2, and Y3 into the quantity of heat, Efficiencies 1 and 2 are shown below:
Efficiency 1=(Y1+Y2)/X1
Efficiency 2=Y3/X2
Here, Efficiency 1 indicates an efficiency of the first boiler 5611, the control valve 5612, the turbine 5613, and the generator 5614, and Efficiency 2 indicates an efficiency of the second boiler 5612.
Generally, plant devices vary in efficiency with loads, so that Formulas 1e, 1f, and 1g indicate efficiency variations due to such loads. The turbine 5613 is a back-pressure turbine, and a part of the given steam energy is used to drive the generator 5614 for the generation output 5635, and the remainder (lost energy excluded) is used to supply steam to the steam load facility 5617.
Among the constraint function Formulas 1b to 1g, Formulas 1e, 1f, and 1g expressing the efficiencies of plant devices are a process operation characteristic function. Here, ai(j); i=1, 2, 3; j=0, 1, 2 indicate process operation characteristic function parameters and are stored in the optimization model storage unit 5601.
Decision of the optimal operating point means to decide the values of the variables X1, X2, Y1, Y2, and Y3 for minimizing the objective function value expressed by Formula 1a, which meet, for example, the constraint functions expressed by Formulas 1b to 1g.
As a tool for solving an optimization problem expressed by a numerical formula model such as Formula 1, for example, there is xe2x80x9cNUOPT-Modeling Language SIMPLE by MATHEMATICAL SYSTEMS, INC.xe2x80x9d available.
It is assumed that the values of the variables X1, X2, Y1, Y2, and Y3 decided by the optimal operation decision means 5602 are X1*, X2*, Y1*, Y2*, and Y3*, respectively. The values X1*, X2*, Y1*, Y2*, and Y3* indicate the optimal operating point for the process operation. In this example, as shown by Formulas 1d to 1g, when one of the five variables (X1, X2, Y1, Y2, and Y3) is decided, the residual four variables are decided.
In an example of the prior art, as shown in FIG. 56, the optimal operation decision means 5602 decides the optimal value Y2* for the variable Y2 corresponding to the generation output 5635 of the generator 5614, that is, an optimal generator output 5631 based on Formula 1, and outputs the decided optimal generator output 5631 to the generator output control means 5605. The generator output control means 5605 outputs a generator output control output 5634 to the control valve 5612 of the turbine 5613 and controls the flow of a steam 5622 at the inlet of the turbine 5613 so that the output 5635 of the generator 5614 becomes equal to the optimal generator output 5631.
The first boiler steam pressure control means 5606 outputs a first boiler steam pressure control output 5632 to the first fuel control valve 5610 and adjusts a first fuel control valve fuel 5620, and thereby controls a steam pressure 5633 at an outlet 5621 of the first boiler 5611 so as to be equal to a given pressure set value. The second boiler steam pressure control means 5607 outputs a second boiler steam pressure control output 5636 to the second fuel control valve 5615 and adjusts the second fuel control valve fuel 5626, and thereby controls a steam pressure 5637 at the outlet 5625 of the second boiler 5616 so as to be equal to a given pressure set value.
In FIG. 56, the operations of the control system 5600 and the process 5609 will be explained qualitatively hereunder. The generator output control means 5605 sends up-output (down-output) 5634 to the control valve 5612 in order to increase (decrease) the generator output 5635 so that the generator output 5635 becomes equal to the optimal generator output 5631.
The up-operation (down-operation) of the control valve 5612 decreases (increases) the steam pressure at the first boiler outlet 5621. The first boiler steam pressure control means 5606 sends the up-output (down-output) 5632 to the first fuel control valve 5610 so as to increase (decrease) the first fuel control valve fuel 5620, thereby to increase (decrease) the decreased (increased) steam pressure. Besides, the up-operation (down-operation) of the control valve 5612 increases (decreases) the steam pressure of each of turbine exhaust 5623, a steam header 5624, and the second boiler outlet 5625.
Then, the second boiler steam pressure control means 5607 sends the down-output (up-output) 5636 to the second fuel control valve 5615 so as to decrease (increase) the second fuel control valve fuel 5626, thereby to decrease (increase) the increased (decreased) steam pressure.
Generally, the steam load facility 5617 requires the steam pressure of the steam header 5624 to be at a predetermined value.
Therefore, as explained above, the control system 5600 controls the steam pressure 5637 at the outlet 5625 of the second boiler 5616, instead of controlling the steam flow generated by the second boiler 5616. As a result, the steam load 5627 required by the steam load facility 5617 becomes equal to the value L given in Formula 1.
Formula 1 expresses the characteristics of the process. As Formula 1 approximates to an actual process more and more, as a result of the control by the control system 5600, when the steam load 5627 is close to L given in Formula 1, the flow (X1) of the first fuel control valve fuel 5620, the flow (X2) of the second fuel control valve fuel 5626, the turbine exhaust 5623 (Y1), the generator output 5635 (Y2), and the steam flow (Y3) of the second boiler outlet 5625 approximate to the optimal operating point (X1*, X2*, Y1*, Y2*, and Y3*) decided by the optimal operation decision means 5602, respectively. As a result, the whole process is operated efficiently in the neighborhood of the optimal operating points.
FIG. 61 shows another example of the prior art.
In FIG. 61, the optimal operation decision means 5602 decides the priority of a turbine exhaust pressure control means 5902 and the second boiler steam pressure control means 5607, and outputs a decided priority set value 6109 to a priority display means 6100. The turbine exhaust pressure control means 5902 outputs a turbine exhaust pressure control output 5904 to the control valve 5612, and inputs turbine exhaust pressure 5903 from the turbine exhaust 5623. The second boiler steam pressure control means 5607 outputs the second boiler steam pressure control output 5636 to the second fuel control valve 5615 and inputs the second boiler outlet steam pressure 5637 from the second boiler outlet 5625.
The priority decision method of the optimal operation decision means 5602 is described below. For example, the generator 5614 is operated in a direction to maximize the output thereof for the steam flow L (5627) of the steam load facility 5617 within the range from the minimum flow to the maximum flow in Formula 1. That is, when it is optimal that the turbine 5613 supplies steam to the steam load facility 5617 on a priority basis, the running priority to the turbine exhaust pressure control means 5902 is set higher than that of the second boiler steam pressure control means 5607.
In this case, the priority set value 6109 decided by the optimal operation decision means 5602 is shown in FIG. 62. As shown in FIG. 62, the priority set value 6109 is composed of a priority level section 6201 and a control means section 6202. When the number indicated in the priority level section 6201 is smaller, the priority of the control means corresponding to the control means section 6202 is higher.
Conventionally, in such a case, in order to operate the equipment according to the priority set as mentioned above, when the steam flow supplied to the steam load facility 5617 is lower, the turbine exhaust pressure control means 5902 is manually set to AUTO and the second boiler steam pressure control means 5607 is set to MANUAL.
The turbine exhaust pressure control means 5902 outputs the turbine exhaust control output 5904 to the control valve 5612, and executes automatic control so that the turbine exhaust pressure 5903 becomes equal to a preset steam pressure set value.
On the other hand, the second boiler steam pressure control means 5607 set to MANUAL does not execute automatic control. It manually lowers the second fuel control valve 5615 to a preset lower limit value.
When the steam flow supplied to the steam load facility 5617 is higher and the control valve 5612 is set to the upper limit, the turbine exhaust pressure control means 5902 is manually set to MANUAL and the second boiler steam pressure control means 5607 is set to AUTO.
The turbine exhaust pressure control means 5902 does not execute automatic control. On the other hand, the second boiler steam pressure control means 5607 set to AUTO outputs the second boiler steam pressure control output 5636 to the second fuel control valve 5615, and executes automatic control so that the second boiler outlet steam pressure 5637 becomes equal to a preset steam pressure set value.
By the aforementioned operations, the steam can be supplied to the steam load facility 5617 on the decided priority basis by controlling the steam pressure of the steam header 5624.
In this case, it is assumed that the steam pressure of the turbine exhaust 5623 and that of the second boiler outlet 5625 change in proportion to the steam pressure of the steam header 5624 or are almost the same, and the steam pressure of the steam header 5624 can be controlled by controlling the steam pressure of the turbine exhaust 5623 or the second boiler outlet 5625.
An example of the prior art concerning a case that the number of optimal operating points 5631 as shown in FIG. 56 is one is explained above. A case that there are a plurality of optimal operating points used for control will be explained by referring to FIG. 57.
In FIG. 57, the control system 5600 is composed of the optimization model storage unit 5601, the optimal operation decision means 5602, a steam pressure setting unit 5700, an adder unit 5701, a proportional integral unit 5702, and n gain units (from a first gain unit 5703, - - - , an i-th gain unit 5704, - - - , to an n-th gain unit 5730). The process 5609 is composed of n boiler facilities (from the first fuel control valve 5610 and a first boiler 5611, - - - , an i-th fuel control valve 5705 and an i-th boiler 5706, - - - , to an n-th fuel control valve 5731 and an n-th boiler 5732) and the steam load facility 5617. In this case, an example of an optimization problem equivalent to Formula 1 is given by a following Formula 2. Formula 2 is composed of an objective function formula 2a and constraint function formulas 2b1 to 2dn.
Formula 2
Minimize: X1+ . . . +Xi . . . +Xnxe2x80x83xe2x80x83(2a)
Subject to:
X1minxe2x89xa6X1xe2x89xa6X1maxxe2x80x83xe2x80x83(2b1)
Ximinxe2x89xa6Xixe2x89xa6Ximaxxe2x80x83xe2x80x83(2bi)
Xnminxe2x89xa6Xnxe2x89xa6Xnmaxxe2x80x83xe2x80x83(2bn)
Y1+ . . . +Yi+ . . . +Yn=Lxe2x80x83xe2x80x83(2c)
Y1=a1(0)+a1(1)xc3x97X1+a1(2)xc3x97X12xe2x80x83xe2x80x83(2d1)
Yi=ai(0)+ai(1)xc3x97Xi+ai(2)xc3x97Xi2xe2x80x83xe2x80x83(2di)
Yn=an(0)+an(1)xc3x97Xn+an(2)xc3x97Xn2xe2x80x83xe2x80x83(2dn)
In Formula 2, X1, X1min and X1max indicate the flow, a minimum flow and a maximum flow of the fuel 5620 of the first boiler 5611, respectively. Y1 indicates the steam flow at the outlet 5621 of the first boiler 5611. Xi, Ximin and Ximax indicate a flow, a minimum flow and a maximum flow of a fuel 5720 of the i-th boiler 5706, respectively. Yi indicates a steam flow at an outlet 5721 of the i-th boiler 5706. Xn, Xnmin and Xnmax indicate a flow, a minimum flow and a maximum flow of a fuel 5742 of the n-th boiler 5732, respectively. Yn indicates a steam flow at an outlet 5743 of the n-th boiler 5732. L indicates the steam flow 5627 of the steam load facility 5617. The steam flow 5626 (L) is inputted to the control system 5600 from the process 5609 as a part of the process data input 5638.
In the same way as with the corresponding process shown in FIG. 56, Formulas 2d1 to 2dn is a process operation characteristic function indicating efficiency variations due to loads, and are stored in the optimization model storage unit 5601 as a part of the optimization model 5630 as shown in FIG. 57. It is assumed that the values of the variables X1, . . . , Xn and Y1, - - - , Yn decided by the optimal operation decision means 5602 are X1*, - - - , Xn* and Y1*, - - - , Yn*, respectively. The values X1*, - - - , Xn* and Y1*, - - - , Yn* indicate optimal operating points for the process operation.
As mentioned above, generally, the steam load facility 5617 requires the steam pressure of the steam header 5624 to be at a predetermined value.
Therefore, as shown in FIG. 57, the control system 5600 controls the steam pressure at the outlet 5621 of the first boiler 5611 to the outlet 5743 of the n-th boiler 5732, instead of controlling the steam flow generated by the first to n-th boilers (5611, 5706, 5732). As a result, the steam load 5627 required by the steam load facility 5617 becomes equal to the constant L given in Formula 2. Further, as shown in Formulas 2d1 to 2dn, variables Y1, - - - , Yn are dependent variables of X1, - - - , Xn, respectively, and when X1*, - - - , Xn* are decided, Y1*, - - - , Yn* are decided.
In the prior art, in order to operate the process at the decided optimal operating points X1*, - - - , Xn*, control gains xcex11* , - - - , xcex1n* corresponding to the control gain units 5703, 5704 and 5730 shown in FIG. 57 are set in proportion to the optimal operating points X1, - - - , Xn*, respectively according to the following Formula 3. Here, Formula 3 is composed of Formulas 3a1 to 3an.
Formula 3
xcex11*=Axc3x97X1*xe2x80x83xe2x80x83(3a1)
xcex1i*=Axc3x97X1*xe2x80x83xe2x80x83(3ai)
xcex1n*=Axc3x97Xn*xe2x80x83xe2x80x83(3an)
A symbol A indicates a proportional constant. When the fuel is proportionally allotted in correspondence with the optimal operating points X1*, - - - , Xn* by the gain setting as shown in Formula 3, the process 5609 can be operated in the neighborhood of the optimal operating points.
The process operation characteristic functions stored in the optimization model storage unit 5601 shown in FIG. 56, 61, or 57, that is, the characteristic function parameters a1(0), a1(1), a1(2), - - - , ai(0), ai(1), ai(2), - - - , an(0), an(1), an(2) corresponding to Formulas 1e to 1g and Formulas 2d1 to 2dn are conventionally set by manual calculation or automatically prepared by the process data collected from the process 5609.
FIG. 58 shows a conventional art of the automatic generation of process operation characteristic function parameters 5811. A conventional automatic generation device of the process operation characteristic function parameters 5811 is composed of a process operation data storage means 5801, a process operation data erasing means 5804, a process operation characteristic function generation means 3003, and a process operation data storage unit 5802.
Conventionally, the process operation data storage means 5801 stores the process data input 5638 collected from the process 5609 in the process operation data storage unit 5802. The process operation data erasing means 5804 erases process operation data 3011 which is older in time among the process operation data 3011 stored in the process operation data storage unit 5802 so as to control the number of process operation data 3011 stored in the process operation data storage unit 5802 within a given limit range. The process operation characteristic function generation means 3003 generates process operation characteristic function parameters from the process operation data 3011 stored in the process operation data storage unit 5802, by using, for example, the least squares method.
When the number of optimal operating points is one as shown in FIG. 56, and the response of the second fuel control valve 5615 to the steam pressure of the steam header 5624 is slower than that of the control valve 5612, a problem would arise that the pressure of the steam header 5624 is controlled by a control loop of the slow response, and the resultant delay of the control makes the pressure of the steam header 5624 unstable.
The causes of response delay may be, for example, a large process time constant and a small control gain. In the example shown in FIG. 56, due to the boiler combustion delay, a time constant of the pressure change of the steam header 5624 to the second fuel control valve 5615 is larger than that of the pressure change of the steam header 5624 to the control valve 5612. The former is, for example, several minutes and the latter is, for example, several seconds.
To solve this problem, the optimal fuel flow control system shown in FIG. 60 is available. For simplicity of the explanation, it is assumed that in FIG. 60, the steam pressure at the first boiler outlet 5621 is controlled to a predetermined pressure. Accordingly, the description on the first boiler steam pressure control means 5606 and the first fuel control valve 5610 by the prior art as shown in FIG. 56 is omitted.
In the case of optimal fuel flow control, as shown in FIG. 60, the optimal operation decision means 5602 decides the optimal second fuel flow X2* (5901) according to Formula 1 and outputs it to a second fuel flow control means 5905. The second fuel flow control means 5905 outputs a second fuel flow control output 5907 to the second fuel control valve 5615 for controlling so that a second fuel control valve fuel flow 5906 becomes equal to the decided optimal second fuel flow 5901.
On the other hand, a turbine exhaust pressure control means 5902 sends a turbine exhaust pressure control output 5904 to the control valve 5612 and controls a pressure 5903 of the turbine exhaust 5623 by performing the up- or down-operation for the control valve 5612.
However, this method changes the output of the generator 5614 by the flow of the steam load 5627 used by the steam load facility 5617. Namely, when the flow of the steam load 5627 increases (decreases), the steam pressure of the steam header 5624 and then that of the turbine exhaust 5623 decrease (increase). The turbine exhaust pressure control means 5902 performs the up- (down-) operation for the control valve 5612 so as to increase (decrease) the decreased (increased) steam pressure, and thereby the flow of the turbine inlet steam 5622 increases (decreases).
The increase (decrease) of the flow of the steam increases (decreases) the drive torque of the generator 5614, and thereby increases (decreases) the output of the generator 5614. Namely, when the flow of the steam load 5627 increases (decreases), the output of the generator 5614 increases (decreases).
However, there is a case when it is necessary to generate power within a fixed tolerance, for example, on a power contract, regardless of the flow of the steam load 5627. In this case, if the steam load 5627 is changed, it is desirable to absorb the change by the second boiler 5616. Therefore, when the system shown in FIG. 60 is used, the output of the generator 5614 is controlled by the steam load 5627 of the steam load facility 5617. As a result, the generator 5614 cannot be operated within a fixed tolerance regardless of the steam load 5627.
The prior art shown in FIG. 61 can control the steam pressure of the steam header 5624, according to the priority decided for the turbine exhaust pressure control means 5902 and the second boiler steam pressure control means 5607. But the manual operation as explained above is necessary and a burden is placed on a user.
Next, a problem of the conventional coordinate system where there are a plurality of optimal operating points will be explained by referring to FIG. 57. In FIG. 57, the optimal operation decision means 5602 decides a plurality of optimal operating points, that is, a first fuel control optimal gain 5710, - - - , an i-th fuel control optimal gain 5711, - - - , and an n-th fuel control optimal gain 5740 by Formulas 2 and 3.
It is assumed that, for example, among n boilers, the efficiency of the i-th (i=1, - - - , n) boiler is high (low). In this case, the i-th boiler generates much (less) steam Yi at a lower fuel flow X1 according to Formula 2, and the gain xcex1i of the boiler increases (decreases) according to Formula 3. Therefore, an efficient (inefficient) boiler produces a larger (smaller) control gain.
Generally, the load change of a device is limited. For example, in a drum boiler, the maximum change rate of the generated steam flow is decided by the evaporation amount from water to steam per hour, which is decided by the physical volume of the evaporation drum.
Let the maximum values of the change rates corresponding to the respective outputs (5715 to 5741) of the first gain unit 5703 to the n-th gain unit 5730 which are decided by such limitation of the change rate be evenly assumed as Rmax. Further, in consideration of that each boiler (5611 to 5732) is controlled by a common fuel master 5714, the fuel control optimal gains 5710, - - - , and 5740 decided by the optimal operation decision means 5602 are assumed as xcex11* , - - - , and xcex1n*. It is further assumed that among xcex11*, - - - , and xcex1n*, the maximum gain is xcex1i*. Here, a following Formula 4 is held, which is composed of Formulas (4-1) to (4-n).
Formula 4
xcex1i*xe2x89xa7xcex11*xe2x80x83xe2x80x83(4-1)
xcex1i*xe2x89xa7xcex1n1*xe2x80x83xe2x80x83(4-n)
As the total maximum output change rate RTmax is restricted by the maximum gain xcex1i* , so that a following Formula 5 is held:
RTmax=Rmaxxc3x97((xcex11*/xcex1i*)+ - - - +(xcex1i*/xcex1i*) + - - - +(xcex1n*/xcex1i*))xe2x80x83xe2x80x83(5)
A following Formula 6 is obtained from Formulas 4 and 5.
RTmaxxe2x89xa6Rmaxxc3x97nxe2x80x83xe2x80x83(6)
The equal sign (condition for that the left side is equal to the right side) of Formula 6 is held only when a following Formula 7 is held.
xcex11*= - - - =xcex1i= - - - =xcex1n*xe2x80x83xe2x80x83(7)
From the aforementioned, in the conventional example, the total maximum output change rate RTmax is restricted by the maximum gain xcex1i*, so that it may be smaller than n times the change rate Rmax (nxc3x97Rmax) (when Formula 7 is not held). When the total maximum output change rate RTmax is reduced, a problem arises that the tracking capability of the control system 5600 to the change of the steam load 5627 decreases.
Next, the conventional preparation of process operation characteristic function parameters is made by manual calculation or by the automatic preparation by the means shown in FIG. 58. In the case of manual preparation, problems such as a burden of a preparer and a preparation error by a preparer are imposed.
The problem on automatic preparation will be explained by referring to FIG. 59. The detail of FIG. 34, to which FIG. 59 corresponds, will be explained later. Accordingly, the detailed explanation of FIG. 59 is omitted here. In FIG. 59, for example, when the process operation is continued so that the process input X1 of the operating point is kept within a division 2 (B1 less than X1xe2x89xa6B2), the process operation data 3011 older in time is erased by the process operation data erasing means 5804. As a result, only the process operation data (X, Y) in the division 2 finally remain as shown in FIG. 59. Here, (X, Y) indicates paired process operation data.
In this case, the process operation characteristic function generation means 3003 generates parameters of the process operation characteristic function 5904 in all the divisions (divisions 1, 2, 3) using only the process operation data 3011 in a certain limited division (division 2), so that a problem arises that the accuracy of the process operation characteristic function 5904 to be generated is reduced.
Accordingly, one object of this invention is to provide a process control system which can control a process to be controlled stably with a good response, while the control output of the fast response can be controlled at the optimal operating point.
Another object of this invention is to provide a process control system which can control a process to be controlled stably with a good response in accordance with an optimal priority, while the higher-priority control output is controlled toward the upper limit on a priority basis and the lower-priority control output is controlled toward the lower limit on a priority basis in accordance with the optimal priority.
Another object of this invention is to provide a process control system in which the process operation characteristic function for deciding the optimal priority and/or the optimal operating point can be automatically generated precisely with a given storage capacity for storing the process operation data, and thereby the burden for preparing the process operation characteristic function imposed on an operator can be lightened.
Still another object of this invention is to provide a process control system which can control stably a process to be controlled in accordance with the optimal operating point and/or the optimal priority decided based on the generated process operation characteristic function, with a good response.
A further object of this invention is to provide a process control system in a general control system in which an optimal operating point is converted to a minor loop bias value, and thereby the control gain of the minor loop is not reduced, which can control stably a process to be controlled in proportion to the optimal operating point with a good response.
These and other objects of this invention can be achieved by providing a process control system in a multi-input/output coordinate control system including a main input for executing coordinate control of the main input. The process control system includes, operating point setting means for setting an operating point set value for an operating point of an n-th control output of fast response to the main input, n-th output control means for generating the n-th control output of fast response to control the main input based on the n-th control output, and m-th output control means for generating an m-th control output to control the operating point of the n-th control output so that the operating point of the n-th control output becomes equal to the operating point set value set in the operating point setting means based on the m-th control output, thereby to allow the n-th control output of fast response to operate at the operating point set value by controlling the main input.
According to one aspect of this invention, there is provided a process control system in a multi-input/output coordinate control system including a main input for executing coordinate control of the main input. The process control system includes, higher-priority output control means for generating a higher-priority output to control the main input based on the higher-priority output, lower-priority output control means for generating a lower-priority output to control the main input based on the lower-priority output, lower-priority output block means for blocking the lower-priority output so as to prevent the higher-priority output from reducing before the higher-priority output reaches an upper limit value, and higher-priority output block means for blocking the higher-priority output so as to prevent the lower-priority output from increasing before the lower-priority output of reaches a lower limit value, thereby to control the higher-priority output toward the upper limit value on a priority basis and the lower-priority output toward the lower limit value on a priority basis, while executing coordinate control of the main input.
According to another aspect of this invention, there is provided a process control system including process data input means for inputting process data input from a process to be controlled, a process operation data storage unit for storing process operation data dispersedly, process operation data storage means for storing dispersedly the process data input inputted by the process data input means in the process operation data storage unit as the process operation data, and an optimization model storage unit for storing an optimization model necessary to decide an optimal operating point for process operation or an optimal control priority. The optimization model includes a process operation characteristic function indicating a mutual relationship between the process operation data. The process control system further includes optimal operation decision means for inputting the process data input from the process data input means and for deciding the optimal operating point for the process operation or the optimal control priority based on the inputted process data input and the optimization model stored in the optimization model storage unit, process operation data dispersion erasing means for erasing the process operation data dispersedly on a priority basis, which is old in time, depending on a size of the process operation data among the process operation data stored in the process operation data storage unit, and process operation characteristic function generation means for generating a process operation characteristic function parameter based on the process operation data stored in the process operation data storage unit, and for updating the process operation characteristic function included in the optimization model stored in the optimization model storage unit by the generated process operation characteristic function parameters, thereby to generate the process operation characteristic function necessary to decide the optimal operating point for the process operation by the process operation data recently dispersedly stored in the process operation data storage unit.
According to still another aspect of this invention, there is provided a process control system in a general control system for controlling a plurality of minor loops composed of master value generation means for generating a master value by deviation integration of a process value of main input and a set value for the main input, a plurality of bias setting means for generating bias values corresponding to each minor control loops, respectively and a plurality of addition-subtraction means for generating addition-subtraction results of the master value, minor inputs from the process and the bias values as instruction values for minor outputs of the minor control loops, respectively. The process control system includes an optimization model storage unit for storing an optimization model necessary to decide an optimal operating point for process operation, optimal operation decision means for inputting process data input and for deciding an optimal operating point based on the inputted process data input and the optimization model stored in the optimization model storage unit, and bias conversion means for converting the decided optimal operating point to optimal bias values and for outputting the converted optimal bias values to the bias setting means to give the optimal bias values as the bias values, respectively, thereby controlling the main input without reducing a control gain thereof.